Conventionally, in order to stably supply power to their customers (consumers), energy companies analyze the electrical power demand based on time series data of power usage for each unit time collected from the respective consumers, and adjust the power generation amount or adjust the power from the electric power exchange based on the analysis result.
In relation to this kind of analytical processing of the electrical power demand, for example, PTL 1 discloses a similarity analysis evaluation system which extracts the feature quantity focusing on the shape of the time series data, performs arbitrary classification based on the extracted feature quantity, and performs relevance evaluation based on the attribute of the time series data and the classification result.
Furthermore, PTL 2 discloses a load curve estimation system which categories a plurality of consumers into groups in which the consumption pattern of resources is similar, generates, for each group, a standard load curve representing the consumption pattern of resources of that group, identifies the group to which the consumer to be subject to estimation belongs, and estimates the resource consumption of the consumer to be subject to estimation for each unit time within an arbitrary period by using the standard load curve of the identified group.